Configuration

FUJISAN

FUJISAN predicts whether two proteins catalyse the same enzymatic reaction using sequence, domain and pocket similarities.

Sources

Enhanced prediction of protein functional identity through the integration of sequence and structural features · Abstract (paragraph 1); Results and discussion/Limitations and perspectives (paragraph 1)

1 evaluation · 8 results

How it worksEvaluated procedure (conceptual)

Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings.

Sources

Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1)

Overview

Model type

Gradient-boosted-tree pipeline; this record is the paper-specific evaluated configuration.

Sources

Biological inputs

Pairs of protein sequences and predicted structures with domain and pocket decomposition

Sources

Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Dataset construction (paragraph 1); Results and discussion/Limitations and perspectives (paragraph 1)

Outputs

Same-reaction versus different-reaction classification

Sources

Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Model training and hyperparameter optimization (paragraph 1); Materials and methods/Feature importance/Gini importance (paragraph 1)

Access

Official study implementation and usage documentation: https://github.com/sfujita0601/FUJISAN/blob/588daf65810c49b021af9e47b11ec752986dcb94/README.md. This pinned documentation revision is not automatically the evaluated weight revision.

Sources

sfujita0601/FUJISAN README.md · README.md; installation, model download and usage instructions

limited source coverage · Automated source review, 2026-09-16. All specifications and missing details

Evaluations and results

1 evaluation · 8 results. Different protocols are not a single leaderboard.

Filter evaluations

Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

Applied filters: All linked evaluations

Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	0.943 AUROC unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features; Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, FUJISAN row, AUROC column
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	87% REC (%) percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column REC (%); XML row2 column4
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	0.742 MCC dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column MCC; XML row2 column7
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	87.2% PRE (%) percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column PRE (%); XML row2 column3
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	0.941 AUPR dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column AUPR; XML row2 column9
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	87% ACC (%) percent · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column ACC (%); XML row2 column2
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	0.873 F1 dimensionless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column F1; XML row2 column6
Configuration: FUJISAN	Protocol: Enzyme-pair functional identity: original held-out test (Enzyme functional identity prediction) Dataset: FUJISAN test sub-dataset	13.3% FPR (%) percent · lower Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible	Author-reported evaluation · Source checked Methods, coverage and source FUJISAN: Enzyme functional identity prediction LightGBM FUJISAN and comparison methods; predictions thresholded to maximizeF 1. Protein-pair splitting is not evidence of disjoint proteins or families. 41,600 protein pairs; balanced functional-identity classes; random 56.25/18.75/25% training/validation/test split. Aggregation: Not reported Enhanced prediction of protein functional identity through the integration of sequence and structural features · Table 1, row FUJISAN, column FPR (%); XML row2 column5

Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.

Use this model

How it works, versions and access

How it works

How the evaluated method works

Features include full-sequence similarity, domain structural similarity and pocket similarity from AlphaFold2 structural models. A LightGBM classifier combines these comparisons.

Sources

What was evaluated

The linked evaluation record identifies FUJISAN: Enzyme functional identity prediction. Its dataset, split, adaptation and evidence origin remain attached to the reported results.

Sources

Enhanced prediction of protein functional identity through the integration of sequence and structural features · The named evaluation’s methods and comparison table; exact preserved evaluation IDs: evaluation-lit-019

Strengths, limitations and unresolved questions

Strengths and limitations

Strengths and considerations

Combines sequence and structure information and exposes feature importance for the trained classifier.
Sources
Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Feature importance/Gini importance (paragraph 1); Materials and methods/Feature importance/Shapley additive explanations (paragraph 1)

Limitations and conditions

Pairs with uncomputable features are excluded, and the random-pair split must not be interpreted as a guaranteed unseen-protein split.
Sources
Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Feature engineering/Full-length sequence similarity features (paragraph 1); Materials and methods/Model training and hyperparameter optimization (paragraph 1)

Profile review details

Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction.

Stable record: reported-model-9c10fbec02a365

Specifications

Inputs, training, access and other details

Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.

Inputs, outputs and configuration
Property	Description and evidence
Model type	Gradient-boosted-tree pipeline; this record is the paper-specific evaluated configuration. Sources Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1)
Architecture / procedure	Features include full-sequence similarity, domain structural similarity and pocket similarity from AlphaFold2 structural models. A LightGBM classifier combines these comparisons. Sources Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1)
Biological inputs	Pairs of protein sequences and predicted structures with domain and pocket decomposition Sources Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Dataset construction (paragraph 1); Results and discussion/Limitations and perspectives (paragraph 1)
Outputs	Same-reaction versus different-reaction classification Sources Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Model training and hyperparameter optimization (paragraph 1); Materials and methods/Feature importance/Gini importance (paragraph 1)
Parameters	An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sources Sources (2) Enhanced prediction of protein functional identity through the integration of sequence and structural features; sfujita0601/FUJISAN README.md · Materials and methods/Dataset construction; Materials and methods/Feature engineering/Full-length sequence similarity features; Materials and methods/Feature engineering/Domain structural similarity features; Materials and methods/Feature engineering/Pocket similarity features; Materials and methods/Model training and hyperparameter optimization; Materials and methods/Performance assessment; Materials and methods/Prediction with DeepFRI; Materials and methods/Prediction with ESM-2; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision
Known versions / configuration	FUJISAN is the comparison-table label; that label does not specify an immutable weight revision. · Not reported in inspected sources Sources Enhanced prediction of protein functional identity through the integration of sequence and structural features · Model identification in the comparison table and corresponding Methods; immutable checkpoint revision is not supplied by the table label.
Training data / fitting	20,800 same-function and 20,800 different-function pairs; train/validation/test proportions are 56.25%, 18.75% and 25%. Sources Enhanced prediction of protein functional identity through the integration of sequence and structural features · Materials and methods/Model training and hyperparameter optimization (paragraph 1); Results and discussion/Performance on low sequence similarity dataset (paragraph 1)
Context limits	A maximum input/context length for this exact evaluated configuration is not established by the inspected sources. · Not reported in inspected sources Sources (2) Enhanced prediction of protein functional identity through the integration of sequence and structural features; sfujita0601/FUJISAN README.md · Materials and methods/Dataset construction; Materials and methods/Feature engineering/Full-length sequence similarity features; Materials and methods/Feature engineering/Domain structural similarity features; Materials and methods/Feature engineering/Pocket similarity features; Materials and methods/Model training and hyperparameter optimization; Materials and methods/Performance assessment; Materials and methods/Prediction with DeepFRI; Materials and methods/Prediction with ESM-2; inspected for explicit maximum input length (dataset lengths and family-wide limits are not substituted); README.md at pinned repository revision
Access	Official study implementation and usage documentation: https://github.com/sfujita0601/FUJISAN/blob/588daf65810c49b021af9e47b11ec752986dcb94/README.md. This pinned documentation revision is not automatically the evaluated weight revision. Sources sfujita0601/FUJISAN README.md · README.md; installation, model download and usage instructions
Code licence	No explicit code licence was established from the paper’s availability statement and inspected repository-root documentation. · Not reported in inspected sources Sources sfujita0601/FUJISAN README.md · README.md and repository-root licence-file search
Weights licence	The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. · Not reported in inspected sources Sources sfujita0601/FUJISAN README.md · README.md; checkpoint/access documentation and licence scope

Evidence

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

21 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statement	Original source and location	Review and provenance
Diagram caption Conceptual input–method–output guide. Check the procedure text and linked evaluation for fitted components, additional inputs and exact settings. Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.caption` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram steps Pairs of protein sequences and predicted structures with domain and pocket decomposition FUJISAN Same-reaction versus different-reaction classification Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.steps` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Diagram title Evaluated procedure (conceptual) Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.diagram.title` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Model type Gradient-boosted-tree pipeline; this record is the paper-specific evaluated configuration. Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.0.value` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Architecture / procedure Features include full-sequence similarity, domain structural similarity and pocket similarity from AlphaFold2 structural models. A LightGBM classifier combines these comparisons. Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.1.value` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Weights licence The inspected model-access documentation does not explicitly identify terms for this exact evaluated checkpoint or fitted head; repository code terms are shown separately. Individual claims	sfujita0601/FUJISAN README.md Original source ↗ README.md; checkpoint/access documentation and licence scope Version: 588daf65810c49b021af9e47b11ec752986dcb94 Retrieved: 2026-09-16T19:54:15.262300+00:00	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.10.value` Source artifact SHA-256: `cb023829651bce1023dd11f603db6731efbff534e04e863821b8677fcec5a19e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Biological inputs Pairs of protein sequences and predicted structures with domain and pocket decomposition Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Dataset construction (paragraph 1); Results and discussion/Limitations and perspectives (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.2.value` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Outputs Same-reaction versus different-reaction classification Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Model training and hyperparameter optimization (paragraph 1); Materials and methods/Feature importance/Gini importance (paragraph 1) Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	source checked automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.3.value` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims	sfujita0601/FUJISAN README.md Original source ↗ Materials and methods/Dataset construction; Materials and methods/Feature engineering/Full-length sequence similarity features; Materials and methods/Feature engineering/Domain structural similarity features; Materials and methods/Feature engineering/Pocket similarity features; Materials and methods/Model training and hyperparameter optimization; Materials and methods/Performance assessment; Materials and methods/Prediction with DeepFRI; Materials and methods/Prediction with ESM-2; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: 588daf65810c49b021af9e47b11ec752986dcb94 Retrieved: 2026-09-16T19:54:15.262300+00:00	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `cb023829651bce1023dd11f603db6731efbff534e04e863821b8677fcec5a19e` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Parameters An aggregate parameter total for this exact evaluated configuration is not established by the inspected sources. Individual claims	Enhanced prediction of protein functional identity through the integration of sequence and structural features Original source ↗ Materials and methods/Dataset construction; Materials and methods/Feature engineering/Full-length sequence similarity features; Materials and methods/Feature engineering/Domain structural similarity features; Materials and methods/Feature engineering/Pocket similarity features; Materials and methods/Model training and hyperparameter optimization; Materials and methods/Performance assessment; Materials and methods/Prediction with DeepFRI; Materials and methods/Prediction with ESM-2; inspected for aggregate parameter count (component sizes are not added without an exact configuration); README.md at pinned repository revision Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: PMC11609699.1 Retrieved: 2026-09-16T10:33:35.728Z	unreported automated source review · 2026-09-16 Audit details Primary full text and the available official implementation/model documentation were inspected. Explanatory claims are source-backed; unresolved exact-configuration metadata is labelled explicitly. This is automated review, not a human review or independent benchmark reproduction. Field: `attributes.profile.facts.4.value` Source artifact SHA-256: `db33e0542005ffae00cd644dfe697185b94c8823d5aee2768620a6db0c48e56f` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Release 2026-09-29-06401fd5b220 · Record review: needs review

2 source records and release history

Enhanced prediction of protein functional identity through the integration of sequence and structural features · Original source · PMC11609699.1
sfujita0601/FUJISAN README.md · Original source · 588daf65810c49b021af9e47b11ec752986dcb94

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Technical metadata and extraction receipts

Stable ID: reported-model-9c10fbec02a365

areas: proteins-complexes
entity level: method
version: Not reported
reported name: FUJISAN
historical missing metadata: version: not_reported_in_legacy_extract; checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: not_reported_in_legacy_extract
metadata review scope: historical_missing_metadata preserves the original discovery state. Current descriptive evidence and missingness are recorded in profile.facts; numerical-result review is separate.
legacy kinds: model
entity classification: review date: 2026-09-17; rationale: This source-scoped entry preserves the method/configuration actually named in an evaluation. It is neither a global family identity nor proof of an immutable checkpoint; the linked evaluation retains adaptation, fitting and scoring details.; source ids: fujisan-2024; source locator: Materials and methods/Feature engineering/Pocket similarity features (paragraph 1); Conclusions (paragraph 1) | Abstract (paragraph 1); Results and discussion/Limitations and perspectives (paragraph 1); ambiguities: Configuration means the source-labelled evaluated identity. It does not establish missing checkpoint hashes, default settings or equivalence to same-named records in other papers.

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model: FUJISAN: Enzyme functional identity prediction

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